Jun 13, 2024 · In this work, we propose a novel Attention-based prefetching framework to accelerate graph analytics applications.

In this work, we propose a novel Attention-based prefetching framework to accelerate graph analytics applications. To achieve high-performance memory access ...

Jun 13, 2024 · Data prefetching is a crucial technique to hide memory access latency by predicting and fetching data into the memory cache beforehand.

Phases, Modalities, Spatial and Temporal Locality: Domain Specific ML Prefetcher for Accelerating Graph Analytics. P Zhang, R Kannan, VK Prasanna. Proceedings ...

... Accelerating Graph Analytics Using Attention-Based Data Prefetcher | Graph analytics shows promise for solving challenging problems on relational data.

Accelerating Graph Analytics Using Attention-Based Data Prefetcher · Author Picture Pengmiao Zhang. https://ror.org/03taz7m60University of Southern California ...

Graph analytics is typically memory-bound. One way to hide the memory access latency is through data prefetching, which relies on accurate memory access ...

Dec 10, 2022 · We propose MPGraph, an ML-based Prefetcher for Graph analytics using domain specific models. MPGraph introduces three novel optimizations.

prefetcher. Accelerating Graph Analytics. By accurately pre-. dicting memory access using A2P, data can be loaded. into a cache from the main memory before ...

We propose MPGraph, an ML-based Prefetcher for Graph analytics using domain specific models. MPGraph introduces three novel optimizations: soft detection ...